THIS SUMMER IN DH
A long, unorganized list of things to catch up on!

There is a lot of competition for the biggest DH conversation of the summer, but the LARB interview series is *perhaps* at the lead. Leading DH practitioners, supporters, and critics weigh in on the state of the field, the popular frustrations with DH, and work being done. The best contribution of the series might be its recognition of just how big the DH umbrella is. As they write, “‘digital humanities’ seems astoundingly inappropriate for an area of study that includes, on one hand, computational research, digital reading and writing platforms, digital pedagogy, open-access publishing, augmented texts, and literary databases, and on the other, media archaeology and theories of networks, gaming, and wares both hard and soft.”

The election: in tweets

David Robinson, “Text analysis of Trump’s tweets confirms he writes only the (angrier) Android half”
Have you seen this data analysis of Trump’s tweets? Data scientist David Robinson, analyzed Trump’s Twitter feed to argue that when Trump tweets himself, he uses more bombastic language than when someone from his campaign tweets. On the one hand – more computational nonsense confirming common sense. On the other – a well articulated and executed case study in data analysis. Worth a read.

Consider this a follow up to last year’s event about art, creativity and artificial intelligence: how Britain’s Tate Museum is using artificial intelligence to match digitized artwork to contemporary news and photojournalism.

An update on Neatline from UVA TodayKatie McNally reports on Neatline, a spatial-temporal exhibition mapping software at the University of Virginia. Neatline works as a plug in for Omeka and can provide a platform for layering geographic, narrative, and visual meaning.

Maxine Joselow, “Labs are for Humanities, too” Inside Higher EdWhat’s with all the DH labs, centers, and commons (like our own new Digital Scholarship Commons)? An exploration on what labs bring to humanities work.

DH TUTORIALS
Jump back in to building and experimenting

the sourcecaster by Thomas Padilla and James BakerA guide to help you use the command line to work through common challenges that come up when working with digital primary sources, including: how to turn a bunch of PDFs into machine readable TIFFs.

An intro to Machine LearningA visual introduction to machine learning built with #D3. Worth a look if only to check out the possibilities for data visualization!

DH OPPORTUNITIES
Grants, Webinars, Conferences, Jobs, Postdocs

Opportunities on Campus

Digital Instruction Project | Find more details & apply >
The Digital Scholarship Commons and Center for Innovations in Teaching and Learning (CITL) will be launching a year long opportunity for faculty and instructors to develop and implement new, engaging assignments. Work with us and a cohort of your peers to brainstorm and then refine a new digital assignment for a Winter 2017 course.